CN113743337A - Image signal capturing platform using depth of field analysis - Google Patents
Image signal capturing platform using depth of field analysis Download PDFInfo
- Publication number
- CN113743337A CN113743337A CN202111053156.2A CN202111053156A CN113743337A CN 113743337 A CN113743337 A CN 113743337A CN 202111053156 A CN202111053156 A CN 202111053156A CN 113743337 A CN113743337 A CN 113743337A
- Authority
- CN
- China
- Prior art keywords
- person object
- falling
- depth
- field
- moving person
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 238000004458 analytical method Methods 0.000 title abstract description 14
- 238000003384 imaging method Methods 0.000 claims abstract description 52
- 230000005540 biological transmission Effects 0.000 claims description 2
- 238000013500 data storage Methods 0.000 claims description 2
- 230000003321 amplification Effects 0.000 abstract description 3
- 238000003199 nucleic acid amplification method Methods 0.000 abstract description 3
- 238000001514 detection method Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
- G06T3/4038—Image mosaicing, e.g. composing plane images from plane sub-images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
- G06T2200/32—Indexing scheme for image data processing or generation, in general involving image mosaicing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30196—Human being; Person
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30221—Sports video; Sports image
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Strategic Management (AREA)
- Game Theory and Decision Science (AREA)
- Multimedia (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Signal Processing (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Image Analysis (AREA)
Abstract
The invention relates to an image signal capturing platform using depth of field analysis, the platform comprising: the first capturing device is used for detecting each moving person object in the received instant splicing picture; the second capturing device is connected with the first capturing device and used for identifying the imaging depth of field value corresponding to each moving person object in the instant splicing picture; and the third capturing device is connected with the second capturing device and used for judging that a certain moving person object is a falling person object when the difference value between the imaging depth of field value of the certain moving person object in the instant splicing picture and the imaging depth of field value of each other surrounding moving person object is over limit. The image signal capturing platform utilizing the depth of field analysis has effective detection and reliable distribution, and can determine the resource quota amplification value of the single falling sporter object according to the single falling pass degree of each sporter object in the field track.
Description
Technical Field
The invention relates to the field of video signal analysis, in particular to an image signal capturing platform utilizing depth of field analysis.
Background
Depth of field (DOF) is the range of distance between the front and back of a subject measured at the front edge of a camera lens or other imager to enable a sharp image to be obtained. The distance from the aperture, lens, and focal plane to the subject is an important factor affecting the depth of field. After the focusing is completed, the distance of the sharp image presented in the range before and after the focal point, this range after, is called the depth of field.
There is a space with a certain length in front of the lens (in front of and behind the focus), and when the object is in the space, the image on the negative film is just between the same circle of confusion. The length of the space in which the subject is located is called the depth of field. In other words, the subject in this space, whose image blur degree appears on the film side, is within the limited range of the allowable circle of confusion, and the length of this space is the depth of field. Currently, sports players on field tracks are often numerous and have relatively limited service resources, resulting in frequent loss of service resources when performing track management. Generally, the group running personnel who do not have the falling bill can deal with each other, the probability of the occurrence of the safety accident is small, the needed service resources are few, the falling bill personnel lack the other personnel to deal with, the probability of the occurrence of the safety accident is large, and the needed service resources are many.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides an image signal capturing platform utilizing depth of field analysis, which can identify the drop-off degree of each competitor in the field track, allocate more event service resources for the dropped-off competitor and allocate less event service resources for the non-dropped-off competitor, thereby realizing the reasonable flow of limited event service resources.
Compared with the prior art, the invention at least has the following prominent substantive characteristics:
(1) determining a resource quota amplification value for the order falling sportsman based on the single falling pass degree of the order falling sportsman, wherein the determined resource quota amplification value for the order falling sportsman is in positive correlation with the single falling pass degree of the order falling sportsman, so that the directional distribution of field race event resources is realized;
(2) and judging whether the certain sportsman belongs to the falling order sportsman or not according to the difference value between the imaging depth of field value of the sportsman in the field track and the imaging depth of field value of the surrounding sportsman.
According to an aspect of the present invention, there is provided an image signal capturing platform using depth of field resolution, the platform comprising:
the first capturing device is used for detecting each moving person object in the received instant splicing picture;
and the second capturing device is connected with the first capturing device and is used for identifying the imaging depth value corresponding to each moving person object in the instant splicing picture.
More specifically, in the image signal capturing platform using depth of field resolution, the platform further includes:
and the third capturing device is connected with the second capturing device and used for judging that a certain moving person object is a falling person object when the difference value between the imaging depth of field value of the certain moving person object in the instant splicing picture and the imaging depth of field value of each other surrounding moving person object is over limit.
More specifically, in the image signal capturing platform using depth of field resolution, the platform further includes:
the Bluetooth communication mechanism is connected with the third capturing device and is used for sending the service resource distributed by each falling person and the service resource distributed by each non-falling person object to a remote supervision server through a Bluetooth communication link;
the intelligent adjusting device is connected with the third capturing device and used for distributing more service resources to each person falling object and distributing less service resources to each person non-falling object;
the wireless transceiving interface is arranged at the far end of the field track and used for sending an acquisition execution instruction or an acquisition stop instruction under manual control;
the track video recording device comprises cameras which are uniformly distributed at different positions of the field track, is connected with the wireless transceiving interface and is used for executing image acquisition action on the track area which is respectively responsible for the cameras when receiving the acquisition execution instruction so as to obtain the partitioned image of each track;
the data combination component is respectively connected with the cameras and the first capturing device and is used for executing image picture splicing processing on the received track subarea images to obtain instant spliced pictures;
wherein, to each person object that falls more distribution service resources, to each person object that does not fall less distribution service resources includes: the amount of service resources which are more distributed to each falling person object is in monotonous positive correlation with the falling single pass degree of the falling person object;
wherein, the monotonous positive correlation between the amount of the service resources which are distributed to each falling person object and the falling single pass degree of the falling person object comprises the following steps: when the difference of the imaging depth of field value of a certain falling person object and the imaging depth of field value of each other surrounding moving person object is larger, the falling single-pass degree of the falling person object is larger;
the third capturing device is further used for judging that a certain moving person object is a non-falling person object when the difference value between the imaging depth of field value of the certain moving person object in the instant splicing picture and the imaging depth of field values of other surrounding moving person objects is not over-limit;
wherein, the monotonous positive correlation between the quota of the service resource which is less distributed to each non-falling person object and the non-falling single pass of the non-falling person object comprises the following steps: when the difference of the imaging depth of field value of a certain non-falling person object and the imaging depth of field value of each other surrounding moving person object is smaller, the non-falling single pass degree of the non-falling person object is larger;
when the difference value between the imaging depth of field value of a certain moving person object in the instant splicing picture and the imaging depth of field value of each other moving person object around exceeds the limit, the step of judging that the certain moving person object is a falling person object comprises the following steps: and when the difference value between the imaging depth of field value of a certain moving person object in the instant splicing picture and the imaging depth of field value of each other surrounding moving person object is more than or equal to a preset difference limit value, judging that the certain moving person object is a person falling object.
The image signal capturing platform utilizing the depth of field analysis has effective detection and reliable distribution. Because the single degree of falling of each contestant in the field track can be identified, more event service resources are distributed for the single person falling, and less event service resources are distributed for the single person not falling, the utilization rate of the event service resources is improved.
Drawings
Embodiments of the invention will now be described with reference to the accompanying drawings, in which:
fig. 1 is a schematic structural diagram illustrating an image signal capturing platform using depth of field resolution according to an embodiment of the present invention.
Detailed Description
Embodiments of an image signal capturing platform using depth of field resolution according to the present invention will be described in detail with reference to the accompanying drawings.
When the lens of the camera is focused clearly on an object, points on the same plane perpendicular to the lens axis at the position opposite to the center of the lens can form a relatively clear image on a film or a receiver, points in a certain range in front of and behind the plane along the lens axis can also form a relatively clear image point acceptable by eyes, and the distance between all scenes in front of and behind the plane is called the depth of field of the camera. When light rays with parallel optical axes enter the convex lens, the ideal lens is that all light rays are converged at one point and then spread out in a cone shape, and the point where all light rays are converged is called a focal point.
Before and after the focus, the light starts to gather and diffuse, and the image of the spot becomes blurred, forming an enlarged circle, known as a circle of confusion. Currently, sports players on field tracks are often numerous and have relatively limited service resources, resulting in frequent loss of service resources when performing track management. Generally, the group running personnel who do not have the falling bill can deal with each other, the probability of the occurrence of the safety accident is small, the needed service resources are few, the falling bill personnel lack the other personnel to deal with, the probability of the occurrence of the safety accident is large, and the needed service resources are many.
In order to overcome the defects, the invention builds an image signal capturing platform by using depth of field analysis, and can effectively solve the corresponding technical problem.
Fig. 1 is a schematic structural diagram illustrating an image signal capturing platform using depth of field resolution according to an embodiment of the present invention, the platform including:
the first capturing device is used for detecting each moving person object in the received instant splicing picture;
and the second capturing device is connected with the first capturing device and is used for identifying the imaging depth value corresponding to each moving person object in the instant splicing picture.
Next, the detailed structure of the image signal capturing platform using depth of field analysis according to the present invention will be further described.
The image signal capturing platform using depth of field resolution may further include:
and the third capturing device is connected with the second capturing device and used for judging that a certain moving person object is a falling person object when the difference value between the imaging depth of field value of the certain moving person object in the instant splicing picture and the imaging depth of field value of each other surrounding moving person object is over limit.
The image signal capturing platform using depth of field resolution may further include:
the Bluetooth communication mechanism is connected with the third capturing device and is used for sending the service resource distributed by each falling person and the service resource distributed by each non-falling person object to a remote supervision server through a Bluetooth communication link;
the intelligent adjusting device is connected with the third capturing device and used for distributing more service resources to each person falling object and distributing less service resources to each person non-falling object;
the wireless transceiving interface is arranged at the far end of the field track and used for sending an acquisition execution instruction or an acquisition stop instruction under manual control;
the track video recording device comprises cameras which are uniformly distributed at different positions of the field track, is connected with the wireless transceiving interface and is used for executing image acquisition action on the track area which is respectively responsible for the cameras when receiving the acquisition execution instruction so as to obtain the partitioned image of each track;
the data combination component is respectively connected with the cameras and the first capturing device and is used for executing image picture splicing processing on the received track subarea images to obtain instant spliced pictures;
wherein, to each person object that falls more distribution service resources, to each person object that does not fall less distribution service resources includes: the amount of service resources which are more distributed to each falling person object is in monotonous positive correlation with the falling single pass degree of the falling person object;
wherein, the monotonous positive correlation between the amount of the service resources which are distributed to each falling person object and the falling single pass degree of the falling person object comprises the following steps: when the difference of the imaging depth of field value of a certain falling person object and the imaging depth of field value of each other surrounding moving person object is larger, the falling single-pass degree of the falling person object is larger;
the third capturing device is further used for judging that a certain moving person object is a non-falling person object when the difference value between the imaging depth of field value of the certain moving person object in the instant splicing picture and the imaging depth of field values of other surrounding moving person objects is not over-limit;
wherein, the monotonous positive correlation between the quota of the service resource which is less distributed to each non-falling person object and the non-falling single pass of the non-falling person object comprises the following steps: when the difference of the imaging depth of field value of a certain non-falling person object and the imaging depth of field value of each other surrounding moving person object is smaller, the non-falling single pass degree of the non-falling person object is larger;
when the difference value between the imaging depth of field value of a certain moving person object in the instant splicing picture and the imaging depth of field value of each other moving person object around exceeds the limit, the step of judging that the certain moving person object is a falling person object comprises the following steps: and when the difference value between the imaging depth of field value of a certain moving person object in the instant splicing picture and the imaging depth of field value of each other surrounding moving person object is more than or equal to a preset difference limit value, judging that the certain moving person object is a person falling object.
In the image signal capturing platform using depth of field analysis:
the third capturing device is further configured to, when a difference between the imaging depth of field value of a certain moving person object in the instant mosaic picture and the imaging depth of field values of other surrounding moving person objects is not exceeded, determine that the certain moving person object is a non-falling person object, including: the third capturing device is further used for judging that the certain moving person object is a non-falling person object when the difference value between the imaging depth of field value of the certain moving person object in the instant splicing picture and the imaging depth of field values of other surrounding moving person objects is smaller than the preset difference limit value.
The image signal capturing platform using depth of field resolution may further include:
and the frequency division duplex interface is connected with the first capturing device and is used for transmitting the current transmission data of the first capturing device through a frequency division duplex communication line.
The image signal capturing platform using depth of field resolution may further include:
and the ZIGBEE communication equipment is used for establishing wireless communication connection with the first capture device and the second capture device respectively through a wireless communication network.
In the image signal capturing platform using depth of field analysis:
the first capture device and the second capture device are respectively realized by ASIC chips with different models, and the first capture device and the second capture device are integrated on the same printed circuit board.
The image signal capturing platform using depth of field resolution may further include:
and the GPS positioning equipment is arranged at one side of the first acquisition device and is used for providing the current satellite positioning data of the first acquisition device.
The image signal capturing platform using depth of field resolution may further include:
and the data storage mechanism is respectively connected with the first capture device and the second capture device and is used for respectively storing the current output data/current input data of the first capture device and the second capture device.
In addition, in the image signal capturing platform using depth of field analysis, allocating more service resources to each of the falling person objects and allocating less service resources to each of the non-falling person objects includes: more service personnel are allocated to each person falling object, and less service personnel are allocated to each person non-falling object;
and in the image signal capturing platform utilizing depth of field analysis, allocating more service resources to each falling person object, and allocating less service resources to each non-falling person object comprises: more supply material is dispensed for each falling person object and less supply material is dispensed for each non-falling person object.
While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications, equivalent structures and functions.
Claims (9)
1. An image signal capture platform utilizing depth of field resolution, the platform comprising:
the first capturing device is used for detecting each moving person object in the received instant splicing picture;
and the second capturing device is connected with the first capturing device and is used for identifying the imaging depth value corresponding to each moving person object in the instant splicing picture.
2. The image signal capture platform with depth of field resolution of claim 1, wherein the platform further comprises:
and the third capturing device is connected with the second capturing device and used for judging that a certain moving person object is a falling person object when the difference value between the imaging depth of field value of the certain moving person object in the instant splicing picture and the imaging depth of field value of each other surrounding moving person object is over limit.
3. The image signal capture platform with depth of field resolution of claim 2, wherein the platform further comprises:
the Bluetooth communication mechanism is connected with the third capturing device and is used for sending the service resource distributed by each falling person and the service resource distributed by each non-falling person object to a remote supervision server through a Bluetooth communication link;
the intelligent adjusting device is connected with the third capturing device and used for distributing more service resources to each person falling object and distributing less service resources to each person non-falling object;
the wireless transceiving interface is arranged at the far end of the field track and used for sending an acquisition execution instruction or an acquisition stop instruction under manual control;
the track video recording device comprises cameras which are uniformly distributed at different positions of the field track, is connected with the wireless transceiving interface and is used for executing image acquisition action on the track area which is respectively responsible for the cameras when receiving the acquisition execution instruction so as to obtain the partitioned image of each track;
the data combination component is respectively connected with the cameras and the first capturing device and is used for executing image picture splicing processing on the received track subarea images to obtain instant spliced pictures;
wherein, to each person object that falls more distribution service resources, to each person object that does not fall less distribution service resources includes: the amount of service resources which are more distributed to each falling person object is in monotonous positive correlation with the falling single pass degree of the falling person object;
wherein, the monotonous positive correlation between the amount of the service resources which are distributed to each falling person object and the falling single pass degree of the falling person object comprises the following steps: when the difference of the imaging depth of field value of a certain falling person object and the imaging depth of field value of each other surrounding moving person object is larger, the falling single-pass degree of the falling person object is larger;
the third capturing device is further used for judging that a certain moving person object is a non-falling person object when the difference value between the imaging depth of field value of the certain moving person object in the instant splicing picture and the imaging depth of field values of other surrounding moving person objects is not over-limit;
wherein, the monotonous positive correlation between the quota of the service resource which is less distributed to each non-falling person object and the non-falling single pass of the non-falling person object comprises the following steps: when the difference of the imaging depth of field value of a certain non-falling person object and the imaging depth of field value of each other surrounding moving person object is smaller, the non-falling single pass degree of the non-falling person object is larger;
when the difference value between the imaging depth of field value of a certain moving person object in the instant splicing picture and the imaging depth of field value of each other moving person object around exceeds the limit, the step of judging that the certain moving person object is a falling person object comprises the following steps: and when the difference value between the imaging depth of field value of a certain moving person object in the instant splicing picture and the imaging depth of field value of each other surrounding moving person object is more than or equal to a preset difference limit value, judging that the certain moving person object is a person falling object.
4. The image signal capture platform with depth of field resolution of claim 3, wherein:
the third capturing device is further configured to, when a difference between the imaging depth of field value of a certain moving person object in the instant mosaic picture and the imaging depth of field values of other surrounding moving person objects is not exceeded, determine that the certain moving person object is a non-falling person object, including: the third capturing device is further used for judging that the certain moving person object is a non-falling person object when the difference value between the imaging depth of field value of the certain moving person object in the instant splicing picture and the imaging depth of field values of other surrounding moving person objects is smaller than the preset difference limit value.
5. The image signal capture platform with depth of field resolution of claim 4, wherein the platform further comprises:
and the frequency division duplex interface is connected with the first capturing device and is used for transmitting the current transmission data of the first capturing device through a frequency division duplex communication line.
6. The image signal capture platform with depth of field resolution of claim 4, wherein the platform further comprises:
and the ZIGBEE communication equipment is used for establishing wireless communication connection with the first capture device and the second capture device respectively through a wireless communication network.
7. The image signal capture platform with depth of field resolution of claim 4, wherein:
the first capture device and the second capture device are respectively realized by ASIC chips with different models, and the first capture device and the second capture device are integrated on the same printed circuit board.
8. The image signal capture platform with depth of field resolution of claim 4, wherein the platform further comprises:
and the GPS positioning equipment is arranged at one side of the first acquisition device and is used for providing the current satellite positioning data of the first acquisition device.
9. The image signal capture platform with depth of field resolution of claim 4, wherein the platform further comprises:
and the data storage mechanism is respectively connected with the first capture device and the second capture device and is used for respectively storing the current output data/current input data of the first capture device and the second capture device.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111053156.2A CN113743337A (en) | 2021-09-09 | 2021-09-09 | Image signal capturing platform using depth of field analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111053156.2A CN113743337A (en) | 2021-09-09 | 2021-09-09 | Image signal capturing platform using depth of field analysis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113743337A true CN113743337A (en) | 2021-12-03 |
Family
ID=78737358
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111053156.2A Withdrawn CN113743337A (en) | 2021-09-09 | 2021-09-09 | Image signal capturing platform using depth of field analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113743337A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2023189544A1 (en) * | 2022-03-29 | 2023-10-05 | Ｋｙｂ株式会社 | Position estimation device, position estimation method, and program |
| JP7493545B2 (en) | 2022-03-29 | 2024-05-31 | カヤバ株式会社 | Position estimation device, position estimation method, and program |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106551688A (en) * | 2016-11-25 | 2017-04-05 | 云通万讯科技（深圳）有限公司 | A kind of sudden death method for early warning and system for marathon race |
| CN106600098A (en) * | 2016-10-29 | 2017-04-26 | 上海救要救信息科技有限公司 | Method and equipment for realizing dynamic allocation of rescue guaranteed resources |
| CN106781251A (en) * | 2016-12-27 | 2017-05-31 | 佛山潮伊汇服装有限公司 | Fall single alarm method and terminal |
| CN109686049A (en) * | 2019-01-03 | 2019-04-26 | 深圳壹账通智能科技有限公司 | Children fall single based reminding method, device, medium and electronic equipment in public place |
| CN110163453A (en) * | 2019-06-20 | 2019-08-23 | 跑哪儿科技（北京）有限公司 | A kind of resources recharge allocation strategy prediction technique, device, system and storage medium |
| CN112635045A (en) * | 2020-12-26 | 2021-04-09 | 西安科锐盛创新科技有限公司 | Intelligent monitoring system |
| CN113034568A (en) * | 2019-12-25 | 2021-06-25 | 杭州海康机器人技术有限公司 | Machine vision depth estimation method, device and system |
-
2021
- 2021-09-09 CN CN202111053156.2A patent/CN113743337A/en not_active Withdrawn
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106600098A (en) * | 2016-10-29 | 2017-04-26 | 上海救要救信息科技有限公司 | Method and equipment for realizing dynamic allocation of rescue guaranteed resources |
| CN106551688A (en) * | 2016-11-25 | 2017-04-05 | 云通万讯科技（深圳）有限公司 | A kind of sudden death method for early warning and system for marathon race |
| CN106781251A (en) * | 2016-12-27 | 2017-05-31 | 佛山潮伊汇服装有限公司 | Fall single alarm method and terminal |
| CN109686049A (en) * | 2019-01-03 | 2019-04-26 | 深圳壹账通智能科技有限公司 | Children fall single based reminding method, device, medium and electronic equipment in public place |
| CN110163453A (en) * | 2019-06-20 | 2019-08-23 | 跑哪儿科技（北京）有限公司 | A kind of resources recharge allocation strategy prediction technique, device, system and storage medium |
| CN113034568A (en) * | 2019-12-25 | 2021-06-25 | 杭州海康机器人技术有限公司 | Machine vision depth estimation method, device and system |
| CN112635045A (en) * | 2020-12-26 | 2021-04-09 | 西安科锐盛创新科技有限公司 | Intelligent monitoring system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2023189544A1 (en) * | 2022-03-29 | 2023-10-05 | Ｋｙｂ株式会社 | Position estimation device, position estimation method, and program |
| JP7493545B2 (en) | 2022-03-29 | 2024-05-31 | カヤバ株式会社 | Position estimation device, position estimation method, and program |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR100823121B1 (en) | Wireless multi-recorder system | |
| US8736745B2 (en) | Camera | |
| CN108718381B (en) | Image capturing apparatus and method for controlling image capturing apparatus | |
| US10321044B2 (en) | Image pickup apparatus and image pickup system with point image intensity distribution calculation | |
| CN102338972A (en) | Assistant focusing method using multiple face blocks | |
| CN103946731A (en) | Focal point adjustment device, image capture device, and lens barrel | |
| US9473693B2 (en) | Photographic apparatus, camera system and methods for calculating focus control information based on a distance between centers of gravity distributions of light receiving sensitivities | |
| DE10210232A1 (en) | Device for determining the focus state of a taking lens | |
| CN105681644A (en) | Focal distance adjusting method and device and terminal | |
| WO2005022901A1 (en) | Imaging system diagnosis device, imaging system diagnosis program, imaging system diagnosis program product, and imaging device | |
| JP2017215578A (en) | Focus detection device and control method of the same | |
| CN113743337A (en) | Image signal capturing platform using depth of field analysis | |
| CN107147858A (en) | Image processing apparatus and its control method | |
| CN114374800A (en) | Focusing processing method and device, storage medium and electronic device | |
| CN106888353A (en) | A kind of image-pickup method and equipment | |
| US20120147247A1 (en) | Optical system and imaging apparatus including the same | |
| US20120206613A1 (en) | Image capture apparatus | |
| CN105657262A (en) | Image processing method and apparatus | |
| WO2021168707A1 (en) | Focusing method, apparatus and device | |
| CN104484051A (en) | Indoor real-time marketing command method and system based on wearable glasses sight line | |
| JP6941011B2 (en) | Imaging device and its control method, program, storage medium | |
| CN115205110A (en) | Panoramic image splicing method and device, electronic device and storage medium | |
| CN105812835A (en) | Information processing method and electronic device | |
| CN211880472U (en) | Image acquisition device and camera | |
| CN106686375A (en) | Camera hyperfocal distance calculating method and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20211203 |
|
| WW01 | Invention patent application withdrawn after publication |